Jamal Shahrabi

1.9k total citations
54 papers, 1.5k citations indexed

About

Jamal Shahrabi is a scholar working on Artificial Intelligence, Management Science and Operations Research and Industrial and Manufacturing Engineering. According to data from OpenAlex, Jamal Shahrabi has authored 54 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 12 papers in Management Science and Operations Research and 9 papers in Industrial and Manufacturing Engineering. Recurrent topics in Jamal Shahrabi's work include Imbalanced Data Classification Techniques (9 papers), Data Mining Algorithms and Applications (7 papers) and Textile materials and evaluations (5 papers). Jamal Shahrabi is often cited by papers focused on Imbalanced Data Classification Techniques (9 papers), Data Mining Algorithms and Applications (7 papers) and Textile materials and evaluations (5 papers). Jamal Shahrabi collaborates with scholars based in Iran, Malaysia and Sweden. Jamal Shahrabi's co-authors include Esmaeil Hadavandi, Mohammad Amin Adibi, Shahrokh Asadi, Masoud Mahootchi, Reza Hafezi, Peyman Abbaszadeh, Azra Ramezankhani, Farzad Hadaegh, Omid Pournik and Fereidoun Azizi and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and Neurocomputing.

In The Last Decade

Jamal Shahrabi

52 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jamal Shahrabi Iran 20 352 309 296 171 131 54 1.5k
Kai Yang United States 29 306 0.9× 215 0.7× 485 1.6× 164 1.0× 72 0.5× 125 2.9k
Gary R. Weckman United States 20 172 0.5× 212 0.7× 246 0.8× 257 1.5× 166 1.3× 71 1.3k
Congjun Rao China 22 632 1.8× 253 0.8× 124 0.4× 162 0.9× 130 1.0× 88 1.7k
Abbas Ahmadi Iran 21 177 0.5× 296 1.0× 475 1.6× 105 0.6× 63 0.5× 81 1.6k
Nagesh Shukla Australia 28 244 0.7× 451 1.5× 453 1.5× 72 0.4× 261 2.0× 88 3.0k
Der‐Chiang Li Taiwan 27 710 2.0× 900 2.9× 351 1.2× 358 2.1× 117 0.9× 122 2.5k
Maziar Yazdani Australia 27 285 0.8× 359 1.2× 339 1.1× 127 0.7× 95 0.7× 61 2.4k
Yanzhang Wang China 24 231 0.7× 527 1.7× 200 0.7× 81 0.5× 82 0.6× 86 1.7k
René Bañares‐Alcántara United Kingdom 23 84 0.2× 255 0.8× 151 0.5× 261 1.5× 134 1.0× 92 2.3k
Esmaeil Hadavandi Iran 20 604 1.7× 430 1.4× 80 0.3× 346 2.0× 76 0.6× 56 1.6k

Countries citing papers authored by Jamal Shahrabi

Since Specialization
Citations

This map shows the geographic impact of Jamal Shahrabi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jamal Shahrabi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jamal Shahrabi more than expected).

Fields of papers citing papers by Jamal Shahrabi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jamal Shahrabi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jamal Shahrabi. The network helps show where Jamal Shahrabi may publish in the future.

Co-authorship network of co-authors of Jamal Shahrabi

This figure shows the co-authorship network connecting the top 25 collaborators of Jamal Shahrabi. A scholar is included among the top collaborators of Jamal Shahrabi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jamal Shahrabi. Jamal Shahrabi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Aminshahidy, Babak, et al.. (2023). Data-Driven Analysis of Stimulation Treatments Using Association Rule Mining. SPE Production & Operations. 38(3). 552–564. 2 indexed citations
2.
Haghighi, Seyedhamidreza Shahabi, et al.. (2021). Customer Churn Prediction Using Data Mining Techniques for an Iranian Payment Application. 134–138. 5 indexed citations
3.
Shahrabi, Jamal, et al.. (2020). Forecasting multiple-well flow rates using a novel space-time modeling approach. Journal of Petroleum Science and Engineering. 191. 107027–107027. 7 indexed citations
4.
Shahrabi, Jamal, et al.. (2020). Representing a Composing Fuzzy-DEA Model to Measure Knowledge Workers Productivity based upon their Efficiency and Cost Effectiveness. JUCS - Journal of Universal Computer Science. 17. 1390–1411. 2 indexed citations
5.
Derakhshan, Shahram, et al.. (2019). Design Optimization of a Centrifugal Pump Using Particle Swarm Optimization Algorithm. International Journal of Fluid Machinery and Systems. 12(4). 322–331. 14 indexed citations
6.
Adibi, Mohammad Amin & Jamal Shahrabi. (2017). A time-varying quadratic programming for online clustering of streaming data. Pattern Analysis and Applications. 21(4). 967–976. 1 indexed citations
7.
Ramezankhani, Azra, Esmaeil Hadavandi, Omid Pournik, et al.. (2016). Decision tree-based modelling for identification of potential interactions between type 2 diabetes risk factors: a decade follow-up in a Middle East prospective cohort study. BMJ Open. 6(12). e013336–e013336. 39 indexed citations
8.
Asadi, Shahrokh & Jamal Shahrabi. (2016). RipMC: RIPPER for Multiclass Classification. Neurocomputing. 191. 19–33. 17 indexed citations
9.
Aminshahidy, Babak, et al.. (2016). Well-testing model identification using time-series shapelets. Journal of Petroleum Science and Engineering. 149. 292–305. 12 indexed citations
10.
Hadavandi, Esmaeil, Jamal Shahrabi, & Shahaboddin Shamshirband. (2015). A novel Boosted-neural network ensemble for modeling multi-target regression problems. Engineering Applications of Artificial Intelligence. 45. 204–219. 41 indexed citations
11.
Shahrabi, Jamal, et al.. (2015). Investigating Performance and Quality in Electronic Industry via Data Mining Techniques. 4(2). 92–96. 1 indexed citations
12.
Ramezankhani, Azra, Omid Pournik, Jamal Shahrabi, et al.. (2014). Applying decision tree for identification of a low risk population for type 2 diabetes. Tehran Lipid and Glucose Study. Diabetes Research and Clinical Practice. 105(3). 391–398. 56 indexed citations
13.
Soltani, Parham, Jamal Shahrabi, Shahrokh Asadi, Esmaeil Hadavandi, & Majid Safar Johari. (2013). A study on siro, solo, compact, and conventional ring-spun yarns. Part III: modeling fiber migration using modular adaptive neuro-fuzzy inference system. Journal of the Textile Institute. 104(7). 755–765. 29 indexed citations
14.
Salehi, M. & Jamal Shahrabi. (2012). Upgrading Fitness in the Production of Garments. Research Journal of Textile and Apparel. 16(4). 100–105.
15.
Shahrabi, Jamal, et al.. (2012). Rapid Ant based clustering-genetic algorithm (RAC-GA) with local search for clustering problem. International Journal of Industrial Engineering Computations. 3(3). 435–444. 2 indexed citations
16.
Shahrabi, Jamal, et al.. (2010). Application of data mining techniques in stock markets: A survey. Journal of Economics and International Finance. 2(7). 109–118. 44 indexed citations
17.
18.
Shahrabi, Jamal, et al.. (2007). A combined multivariate technique and multi criteria decision making to maintenance strategy selection. 6. 621–625. 8 indexed citations
19.
Shahrabi, Jamal, et al.. (2007). Project Selection By Using Fuzzy Ahp And Topsis Technique. Zenodo (CERN European Organization for Nuclear Research). 199 indexed citations
20.
Shahrabi, Jamal, et al.. (2006). STUDY OF BLOOD LEAD LEVELS, HEMOGLOBIN & PLASMA ASCORBIC ACID IN A CAR COMPANY WELDERS. Iran Occupational Health Journal. 3(12). 50–55. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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